Analysing the demand for rail tyravel to out of town shopping centres

Anzir Boodoo

Summary

This study attempts to provide an analysis of the pattern of rail access
to out of town shopping centres. Out of centre shopping has grown dramatically
in the last 15 years, marked most significantly by the opening of several
large shopping complexes designed to offer a complete shopping experience
under one roof. Environmental concerns have accompanied the car-dominated
nature of access to these centres, which has been partly addressed by improving
public transport access. Many of these centres have rail access either
through their own station or a link bus to a nearby railhead. However,
little is known about the pattern of rail access. The study approaches
the analysis of rail access through the formulation of models to describe
the pattern of rail access to five out of town centres.

Out of town shopping began in the USA from out of town supermarkets
and “strip malls” of shops along a main road. Over time, this form developed
into the fully enclosed shopping centre. In the UK, this began to be developed
from the 1970s onwards, with the Brent Cross Centre in London and new centres
for several of the New Towns. However, it was not until the opening of
MetroCentre in 1986 that its development took on the form recognised today.
In tandem with the construction of these new regional centres, with sizes
around 100,000m2 and two or more large department stores, smaller subregional
centres began to be built serving a smaller catchment, often in suburban
locations in a major city. Other forms of out of town shopping include
retail parks and designer outlet centres, but these are not included in
the study due to their more specialised character.

Regional centres in the UK have tended to be developed on former industrial
land, which has led to many having railway lines nearby. Often the potential
has been exploited for no other reason than its presence, however, following
rail privatisation, Railtrack and the Train Operating Companies serving
an area have an obligation to develop the network for commercial benefit
as well as the regulatory requirements.

Government papers and planning policy guidance have often slated out
of town retail development for being too car dominated and for its negative
impacts on surrounding town centres. However, rising car ownership and
mobility have been leading to the decline of smaller town centres in favour
of larger ones for a very long time. However, it is now government policy
that developments be accessible by a range of transport modes following
the Integrated Transport White Paper of 1998 and the subsequent revision
of many other documents. Shopping is the second most important generator
of trips after journeys to work, and with 50% of all shopping trips made
by car and only 11% by public transport there is clearly a need for shopping
centre managers and transport operators to consider ways in which to develop
public transport access to retail developments.

The study involved a postal sector based model, which was based around
a survey of the postcodes of passengers using rail or rail link buses at
six shopping centres, two subregional (Perry Barr One Stop in Birmingham
and Crystal Peaks in Sheffield), and four regional (Bluewater in Kent,
Meadowhall in Sheffield, MetroCentre in Gateshead and the Trafford Centre
in Manchester), though Bluewater’s results during engineering work were
deemed to be too adversely affected by engineering works for it to be reasonably
included in the analysis.

The postcode survey was subject to disaggregate modelling analysis,
combined with the locations of each centre through a GIS layer and data
sets with a limited set of 1991 Census variables by postal sector and the
locations of UK rail stations. Each sector was mapped onto its Census data
and an origin rail station. The distance and rail service between the origin
station and the shopping centre were then calculated for use in the model
estimation. Estimation involved regression analysis with a log-log model
in order to produce constant elasticities of the number of rail passengers
with respect to the variables in question. This was carried out for all
centres (with either all the data or only origins within 50km of the centre
visited), each centre individually and all sub-regional and all regional
centres together.

Results

There was a reasonable model fit in most cases, with the best models relating
the number of passengers from each sector to the generalised cost of rail
travel, sector population, retirement rates and the level of car ownership,
which operated in the wrong direction to that expected and most likely
functions as a proxy for wealth.

The elasticities broadly agreed in most of the models, suggesting these
was some certainty in the way these variables affect the propensity to
travel by rail. Forecasting was also carried out using a hypothetical data
set in order to illustrate how the models may work in practice.

Meadowhall attacted by far the largest number of passengers, most likely
due to its more focal location on the rail network and frequent local,
express and Supertram services

Major regional centres (such as Meadowhall) have more competition between
other modes of transport (mostly the car), and show this with higher generalised
cost elasticities. They also have more competition with other centres than
the subregional centres (such as Crystal Peaks), which have more local
shopping functions. This is shown by having lower elasticities with respect
to the population of each sector